Ciro Donalek

Probing the Outer Galactic halo with RR Lyrae from the Catalina Surveys

We present analysis of 12,227 type-ab RR Lyraes (RRLs) found among the 200 million public light curves in Catalina Surveys Data Release 1. These stars span the largest volume of the Milky Way ever surveyed with RRLs, covering ~20,000 deg2 of the sky (0° 1500 of the RRLs. Using the accurate distances derived for the RRLs, we show the paths of the Sagittarius tidal streams crossing the sky at heliocentric distances from 20 to 60 kpc. By selecting samples of Galactic halo RRLs, we compare their velocity, metallicity, and distance with predictions from a recent detailed N-body model of the Sagittarius system. We find that there are some significant differences between the distances and structures predicted and our observations.

Immersive and collaborative data visualization using virtual reality platforms

Effective data visualization is a key part of the discovery process in the era of “big data”. It is the bridge between the quantitative content of the data and human intuition, and thus an essential component of the scientific path from data into knowledge and understanding. Visualization is also essential in the data mining process, directing the choice of the applicable algorithms, and in helping to identify and remove bad data from the analysis. However, a high complexity or a high dimensionality of modern data sets represents a critical obstacle. How do we visualize interesting structures and patterns that may exist in hyper-dimensional data spaces? A better understanding of how we can perceive and interact with multidimensional information poses some deep questions in the field of cognition technology and human-computer interaction. To this effect, we are exploring the use of immersive virtual reality platforms for scientific data visualization, both as software and inexpensive commodity hardware. These potentially powerful and innovative tools for multi-dimensional data visualization can also provide an easy and natural path to a collaborative data visualization and exploration, where scientists can interact with their data and their colleagues in the same visual space. Immersion provides benefits beyond the traditional “desktop” visualization tools: it leads to a demonstrably better perception of a datascape geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data.

Evidence for a Milky Way Tidal Stream Reaching Beyond 100?kpc

We present the analysis of 1207 RR Lyrae found in photometry taken by the Catalina Surveys Mount Lemmon telescope. By combining accurate distances for these stars with measurements for ~14,000 type-ab RR Lyrae from the Catalina Schmidt telescope, we reveal an extended association that reaches Galactocentric distances beyond 100 kpc and overlaps the Sagittarius stream system. This result confirms earlier evidence for the existence of an outer halo tidal stream resulting from a disrupted stellar system. By comparing the RR Lyrae source density with that expected based on halo models, we find the detection has ~8σ significance. We investigate the distances, radial velocities, metallicities, and period-amplitude distribution of the RR Lyrae. We find that both radial velocities and distances are inconsistent with current models of the Sagittarius stream. We also find tentative evidence for a division in source metallicities for the most distant sources. Following prior analyses, we compare the locations and distances of the RR Lyrae with photometrically selected candidate horizontal branch stars and find supporting evidence that this structure spans at least 60° of the sky. We investigate the prospects of an association between the stream and the unusual globular cluster NGC 2419.

A systematic search for close supermassive black hole binaries in the Catalina Real-time Transient Survey

Hierarchical assembly models predict a population of supermassive black hole (SMBH) binaries. These are not resolvable by direct imaging but may be detectable via periodic variability (or nanohertz frequency gravitational waves). Following our detection of a 5.2-year periodic signal in the quasar PG 1302−102, we present a novel analysis of the optical variability of 243 500 known spectroscopically confirmed quasars using data from the Catalina Real-time Transient Survey (CRTS) to look for close (<0.1 pc) SMBH systems. Looking for a strong Keplerian periodic signal with at least 1.5 cycles over a baseline of nine years, we find a sample of 111 candidate objects. This is in conservative agreement with theoretical predictions from models of binary SMBH populations. Simulated data sets, assuming stochastic variability, also produce no equivalent candidates implying a low likelihood of spurious detections. The periodicity seen is likely attributable to either jet precession, warped accretion discs or periodic accretion associated with a close SMBH binary system. We also consider how other SMBH binary candidates in the literature appear in CRTS data and show that none of these are equivalent to the identified objects. Finally, the distribution of objects found is consistent with that expected from a gravitational-wave-driven population. This implies that circumbinary gas is present at small orbital radii and is being perturbed by the black holes. None of the sources is expected to merge within at least the next century. This study opens a new unique window to study a population of close SMBH binaries that must exist according to our current understanding of galaxy and SMBH evolution.

A novel variability-based method for quasar selection: evidence for a rest-frame ∼54 d characteristic time-scale

We compare quasar-selection techniques based on their optical variability using data from the Catalina Real-time Transient Survey (CRTS). We introduce a new technique based on Slepian wavelet variance (SWV) that shows comparable or better performance to structure functions and damped random walk models but with fewer assumptions. Combining these methods with Wide-field Infrared Survey Explorer mid-IR colours produces a highly efficient quasar-selection technique which we have validated spectroscopically. The SWV technique also identifies characteristic time-scales in a time series, and we find a characteristic rest-frame time-scale of ∼54 d, confirmed in the light curves of ∼18 000 quasars from CRTS, SDSS and MACHO data, and anticorrelated with absolute magnitude. This indicates a transition between a damped random walk and P(f) ∝ f^(−1/3) behaviours and is the first strong indication that a damped random walk model may be too simplistic to describe optical quasar variability.

A comparison of period finding algorithms

This paper presents a comparison of popular period finding algorithms applied to the light curves of variable stars from the Catalina Real-Time Transient Survey, MACHO and ASAS data sets. We analyse the accuracy of the methods against magnitude, sampling rates, quoted period, quality measures (signal-to-noise and number of observations), variability and object classes. We find that measure of dispersion-based techniques – analysis of variance with harmonics and conditional entropy – consistently give the best results but there are clear dependences on object class and light-curve quality. Period aliasing and identifying a period harmonic also remain significant issues. We consider the performance of the algorithms and show that a new conditional entropy-based algorithm is the most optimal in terms of completeness and speed. We also consider a simple ensemble approach and find that it performs no better than individual algorithms.

Neural networks in astronomy

In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large astronomical databases which is foreseen in the framework of the astrophysical virtual observatory and national virtual observatory projects, is, however, posing unprecedented data mining and visualization problems which will find a rather natural and user friendly answer in artificial intelligence tools based on NNs, fuzzy sets or genetic algorithms. This review is aimed to both astronomers (who often have little knowledge of the methodological background) and computer scientists (who often know little about potentially interesting applications), and therefore will be structured as follows: after giving a short introduction to the subject, we shall summarize the methodological background and focus our attention on some of the most interesting fields of application, namely: object extraction and classification, time series analysis, noise identification, and data mining. Most of the original work described in the paper has been performed in the framework of the AstroNeural collaboration (Napoli-Salerno).

The Palomar-Quest digital synoptic sky survey

We describe briefly the Palomar-Quest (PQ) digital synoptic sky survey, including its parameters, data processing, status, and plans. Exploration of the time domain is now the central scientific and technological focus of the survey. To this end, we have developed a real-time pipeline for detection of transient sources.We describe some of the early results, and lessons learned which may be useful for other, similar projects, and time-domain astronomy in general. Finally, we discuss some issues and challenges posed by the real-time analysis and scientific exploitation of massive data streams from modern synoptic sky surveys.

Cataclysmic variables from the Catalina Real-time Transient Survey

We present 855 cataclysmic variable candidates detected by the Catalina Real-time Transient Survey (CRTS) of which at least 137 have been spectrosc opically confirmed and 705 are new discoveries. The sources were identified from the ana lysis of five years of data, and come from an area covering three quarters of the sky. We study the amplitude distribution of the dwarf novae CVs discovered by CRTS during outburst, and fi nd that in quiescence they are typically two magnitudes fainter compared to the spectr os opic CV sample identified by SDSS. However, almost all CRTS CVs in the SDSS footprint have ugriz photometry. We analyse the spatial distribution of the CVs and find evidence that many of the systems lie at scale heights beyond those expected for a Galactic thin disc population. We compare the outburst rates of newly discovered CRTS CVs with the previously known CV population, and find no evidence for a difference between them. However, we fin d that significant evidence for a systematic difference in orbital period distribution . We discuss the CVs found below the orbital period minimum and argue that many more are yet to be identified among the full CRTS CV sample. We cross-match the CVs with archival X-ray ca talogs and find that most of the systems are dwarf novae rather than magnetic CVs.

Automated probabilistic classification of transients and variables

There is an increasing number of large, digital, synoptic sky surveys, in which repeated observations are obtained over large areas of the sky in multiple epochs. Likewise, there is a growth in the number of (often automated or robotic) follow-up facilities with varied capabilities in terms of instruments, depth, cadence, wavelengths, etc., most of which are geared toward some specific astrophysical phenomenon. As the number of detected transient events grows, an automated, probabilistic classification of the detected variables and transients becomes increasingly important, so that an optimal use can be made of follow-up facilities, without unnecessary duplication of effort. We describe a methodology now under development for a prototype event classification system; it involves Bayesian and Machine Learning classifiers, automated incorporation of feedback from follow-up observations, and discriminated or directed follow-up requests. This type of methodology may be essential for the massive synoptic sky surveys in the future.